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Objectives: To analyze the positional distances covered above generic and individualized speed thresholds within the most demanding phases of match play. Categorized by position, 17 English Premier League players' match data were analyzed over 2 consecutive seasons (2019–20 and 2020–21). The most demanding phases of play were determined using a rolling average across 4 periods of 1, 3, 5, and 10 minutes. Distance covered in the time above the standard speed of 5.5 m/s was analyzed, with individualized metrics based on the maximal aerobic speed (MAS) test data. Results: Central defenders displayed lower values for high-intensity periods when compared with fullbacks, midfielders, and wide midfielders for both generic and individualized metrics. MAS during 1-minute periods was significantly higher for forwards when compared with central defenders (82.9 [18.9] vs 67.5 [14.8] for maximum high-speed running [HSR] and 96.0 [15.9] vs 75.7 [13.8] HSR for maximum MAS activity). The maximum effect size differences between the central midfielders, wide midfielders, and fullbacks for HSR and MAS measures under the maximum HSR criterion was 0.28 and 0.18 for the 1-minute period, 0.36 and 0.19 for the 3-minute period, 0.46 and 0.31 for the 5-minute period, and 0.49 and 0.315 for the 10-minute period. Conclusions: Individualized speed metrics may provide a more precise and comparable measure than generic values. Data appear to be consistent across playing positions except for central defenders. This information may allow practitioners to directly compare individualized physical outputs of non–central defenders during the most demanding phases of play regardless of the players' positional group. This may provide coaches with important information regarding session design, training load, and fatigue monitoring. [ABSTRACT FROM AUTHOR]

Introduction: A promising approach to optimizing recovery in youth football has been the use of machine learning (ML) models to predict recovery states and prevent mental fatigue. This research investigates the application of ML models in classifying male young football players aged under (U)15, U17, and U19 according to their recovery state. Weekly training load data were systematically monitored across three age groups throughout the initial month of the 2019–2020 competitive season, covering 18 training sessions and 120 observation instances. Outfield players were tracked using portable 18-Hz global positioning system (GPS) devices, while heart rate (HR) was measured using 1 Hz telemetry HR bands. The rating of perceived exertion (RPE 6–20) and total quality recovery (TQR 6–20) scores were employed to evaluate perceived exertion, internal training load, and recovery state, respectively. Data preprocessing involved handling missing values, normalization, and feature selection using correlation coefficients and a random forest (RF) classifier. Five ML algorithms [K-nearest neighbors (KNN), extreme gradient boosting (XGBoost), support vector machine (SVM), RF, and decision tree (DT)] were assessed for classification performance. The K-fold method was employed to cross-validate the ML outputs. Results: A high accuracy for this ML classification model (73–100%) was verified. The feature selection highlighted critical variables, and we implemented the ML algorithms considering a panel of 9 variables (U15, U19, body mass, accelerations, decelerations, training weeks, sprint distance, and RPE). These features were included according to their percentage of importance (3–18%). The results were cross-validated with good accuracy across 5-fold (79%). Conclusion: The five ML models, in combination with weekly data, demonstrated the efficacy of wearable device-collected features as an efficient combination in predicting football players' recovery states. [ABSTRACT FROM AUTHOR]

The purpose of the study was to examine the prevalence of the Relative Age Effect (RAE) across an international soccer programme in male and female players aged 12 years old to seniors. One hundred forty-five male (age: 18.8 ± 4.6 years; body mass: 68.1 ± 10.2 kg; body height: 177.3 ± 10.5 cm) and 218 female (age: 15.9 ± 4.6 years; body mass: 66.2 ± 10.5 kg; body height: 170.6 ± 8.3 cm) players from a National Association were assessed. All participants were divided into four quartiles: January to March (BQ1), April to June (BQ2), July to September (BQ3), and October to December (BQ4). The results showed that the distributions for all male squads were significantly skewed, with more players than expected from BQ1 in the U-21, U-19, and U-17 and less players than expected from BQ4 in the U-19 squad. The distributions for all female squads showed significantly more players than expected from BQ1 in the U-16 and less players than expected from BQ4 in the U-14 squad. The distributions across the different positions for the male squads combined were significantly skewed with more forward players than expected from BQ1 and less forward and midfielder players than expected from BQ4. For the female squads, there were significantly more BQ1 defenders from the U-16 squad than expected. In conclusion, this study unveils significant disparities in quartile distributions among male and female squads. Moreover, the data emphasize the potential impact of heightened physical demands in certain positions on the RAE. [ABSTRACT FROM AUTHOR]

The aims of this study were to: a) examine the relationships between high-intensity distances covered above generic and relative speed thresholds in English Premier League (EPL) matches across two consecutive seasons and b) analyze the effects of playing position and team possession. Sixteen elite male soccer players (seven defenders, six midfielders and three forwards) participated in this study (age 27.8 ± 3.5 years, height 183.7 ± 5.4 cm, body mass 83.9 ± 7.1 kg). An Optical Tracking System was used to collect the following variables: total distance covered; high-speed running distance (HSRD) (> 5.5 m/s); high-intensity running distance (HIRD) (5.5--7 m/s); sprint distance (> 7 m/s); total distance covered above Maximal Aerobic Speed (MAS); distance covered > 85% peak speed (PS); and distance > 30% Anaerobic Speed Reserve (ASR). All measures were analyzed as whole match totals and as distances covered in the periods of the team in possession (TIP), opponent team in possession (OTIP), and ball out of play (BOP). Analysis by position based on defenders, midfielders and forwards was also performed. Distance > 30% ASR was almost perfectly correlated with HSRD (r = 0.98), while distances > MAS were highly correlated with both HIRD (r = 0.91) and HSRD (r = 0.91), and distance > 85% PS were highly correlated with SD (r = 0.70). Although the generic and relative speed thresholds show almost perfect correlation, the differences between HSRD, HIRD and distance > MAS indicate that players may be exposed to more HIRD when using relative thresholds. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the effects of a 4-week intervention combining smallsided games (SSGs) and high-intensity interval training (HIIT) on physical fitness in collegiate male soccer players. Methods: Twenty-one soccer players were randomly assigned to either the HIIT + SSGs group (n = 11) or a control group (n = 10). Physical fitness was assessed at baseline and 1-week post-intervention, including countermovement jump (CMJ), change of direction (COD) test, sprint test, repeated sprint ability (RSA) test, and 30-15 Intermittent Fitness Test (30-15IFT). The intervention comprised eight sessions over 4 weeks: four SSGs and four HIIT. Results: The intervention group showed small to moderate improvements: mean RSA improved by 4.5% (p = 0.07), CMJ increased by 3.2% (p = 0.12), and 30-15IFT scores enhanced by 6.8% (p = 0.09). Key predictors of group membership included heart rate load per minute (OR 1.602) and various GPS variables. Conclusion: The 4-week intervention combining SSGs with HIIT did not produce statistically significant improvements in most physical fitness variables compared to the control group. Although there were positive trends in variables such as RSA and 30-15IFT, these changes were modest and not statistically significant. The results suggest that while the combined SSGs and HIIT approach shows potential, its impact on physical fitness over a 4-week period is limited, with some variables, like CMJ, even showing decreases. [ABSTRACT FROM AUTHOR]

This retrospective study aimed to examine the effect of transcranial direct current stimulation (tDCS) combined with lower limb pneumatic compression during the postmatch recovery period in top-level professional male soccer players' physiological and perceptual markers of recovery status. During the 2022 season (baseline), pneumatic compression was performed as part of the recovery strategy, applied the day after official match play and psycho- physiological measurements (pain, sleep, perceived recovery, and creatine kinase [CK] sampling) were performed on the second day postmatch. During the 2023 season, the tDCS protocol was introduced, with its application being performed simultaneously (in conjunction) with pneumatic compression. Recovery sessions following 10 matches in the 2022 season and following 10 matches in the 2023 season were included in the analyses. Compared with 2022 (baseline; pneumatic compression isolated), the players perceived an increased recovery on the second day postmatch when tDCS was used in conjunction with the pneumatic compression (mean = 12%; p = 0.008) and rated improved sleep quality for the nights after applying tDCS combined with pneumatic compression (mean = 7.5%; p = 0.029). On the second day postmatch, a significant reduction was observed in muscle pain/soreness (mean = 64%; p < 0.0001) and the CK concentration decreased when baseline (pneumatic compression isolated) was compared with tDCS + pneumatic compression (mean = 76%; p = 0.001). In summary, combining pneumatic compression with tDCS may enhance the effects of both interventions, leading to greater overall improvements in recovery. Further research is warranted to confirm these findings and explore the underlying mechanisms in more detail. [ABSTRACT FROM AUTHOR]

The aim of this study was to analyze the match-to-match variation in high-intensity demands from one Portuguese professional football team according to playing positions. Twenty-three male outfield professional football players were observed during eighteen matches of the Portuguese Second League. Time–motion data were collected using Global Positioning System (GPS) technology. Match running performance was analyzed based on the following three playing positions: defenders (DF), midfielders (MF), and forwards (FW). Repeated measures ANOVA was utilized to compare match running performance within each position role, and seasonal running variation. Practical differences were assessed using the smallest worthwhile change (SWC), coefficient of variation (CV), and twice the coefficient of variation (2CV). Significant differences were found among playing positions in total distance covered (F = 15.45, p < 0.001, η2 = 0.33), average speed (F = 12.79, p < 0.001, η2 = 0.29), high-speed running (F = 16.93, p < 0.001, η2 = 0.36), sprinting (F = 13.49, p < 0.001, η2 = 0.31), accelerations (F = 4.69, p = 0.001, η2 = 0.132), and decelerations (F = 12.21, p < 0.001, η2 = 0.284). The match-to-match running performance encompassed TD (6.59%), AvS (8.67%), HSRr (37.83%), SPR (34.82%), ACC (26.92%), and DEC (27.85%). CV values for total distance covered ranged from 4.87–6.82%, with forwards and midfielders exhibiting the greatest and smallest variation, respectively. Midfielders demonstrated the highest match-to-match variation for all other analyzed variables (8.12–69.17%). All playing positions showed significant variation in high-demanding variables (26.94–37.83%). This study presents the initial analysis of match-to-match variation in high-intensity demands within a Portuguese professional football team. Thus, the position's specificity and context can provide a helpful strategy for evaluating match-to-match running performance, and for recommending individualized training exercises based on the peak and high-intensity demands for each player's role within the game. [ABSTRACT FROM AUTHOR]

The aim of this study was to test a machine learning (ML) model to predict high-intensity actions and body impacts during youth football training. Sixty under-15, -17, and -19 sub-elite Portuguese football players were monitored over a 6-week period. External training load data were collected from the target variables of accelerations (ACCs), decelerations (DECs), and dynamic stress load (DSL) using an 18 Hz global positioning system (GPS). Additionally, we monitored the perceived exertion and biological characteristics using total quality recovery (TQR), rating of perceived exertion (RPE), session RPE (sRPE), chronological age, maturation offset (MO), and age at peak height velocity (APHV). The ML model was computed by a feature selection process with a linear regression forecast and bootstrap method. The predictive analysis revealed that the players' MO demonstrated varying degrees of effectiveness in predicting their DEC and ACC across different ranges of IQR. After predictive analysis, the following performance values were observed: DEC ( x ¯ predicted = 41, β = 3.24, intercept = 37.0), lower IQR (IQRpredicted = 36.6, β = 3.24, intercept = 37.0), and upper IQR (IQRpredicted = 46 decelerations, β = 3.24, intercept = 37.0). The player's MO also demonstrated the ability to predict their upper IQR (IQRpredicted = 51, β = 3.8, intercept = 40.62), lower IQR (IQRpredicted = 40, β = 3.8, intercept = 40.62), and ACC ( x ¯ predicted = 46 accelerations, β = 3.8, intercept = 40.62). The ML model showed poor performance in predicting the players' ACC and DEC using MO (MSE = 2.47–4.76; RMSE = 1.57–2.18: R2 = −0.78–0.02). Maturational concerns are prevalent in football performance and should be regularly checked, as the current ML model treated MO as the sole variable for ACC, DEC, and DSL. Applying ML models to assess automated tracking data can be an effective strategy, particularly in the context of forecasting peak ACC, DEC, and bodily effects in sub-elite youth football training. [ABSTRACT FROM AUTHOR]

Purpose: The powerful activity profile of elite soccer match play has not been documented appropriately to inform specific maximal power assessment and development criteria. The aims of the current study were to develop a reliable soccer-specific powerful action (SSPA) notational analysis coding system that could be used to compare frequency and durations of powerful actions during elite youth soccer match play. Methods: Sixteen elite male English Premier League (EPL) Academy players (19 ± 1 yrs) were recorded by an individual camera during 16 competitive EPL U18 and U21 games. Video footage was analyzed using performance analysis software and SSPAs were coded according to the following categories: initial acceleration, leading acceleration, sprint, unilateral jump and bilateral jump. Results: The SSPA coding system demonstrated very good inter- and intra-rater reliability (kappa coefficients = 0.827). Elite youth EPL soccer players undertook significantly more initial (31 ± 9) and leading (37 ± 12) accelerations than sprints (8 ± 3; p = 0.014, d = 1.7, and p < 0.001, d = 1.7, respectively) and jumps (6 ± 5; p = 0.002, d = 1.7 and p < 0.001, d = 1.7, respectively). Players performed a significantly greater number of initial and leading accelerations with action durations below 1.5 s compared to above 1.5 s (p = 0.001, d = 1.6, and p = 0.002, d = 1.4), respectively. Conclusions: Our SSPA coding system provides a reliable observational instrument for quantifying the frequency and duration of powerful actions performed during elite soccer match play. In our sample of elite youth soccer players, horizontal accelerations of short duration (< 1.5 s) from different starting speeds appear the most dominant powerful action in elite youth soccer match play.

Background: The relationship between hip strength deficiency in various planes and musculoskeletal injuries within the movement system has been well-established in numerous studies. The present study sought to explore the relationships between hip strength and specific aspects of lower extremity running kinematics. Methodology: To achieve this objective, the three-dimensional running kinematics of 21 male elite middle-distance runners (mean age: 19.7 ± 1.2 years; mean experience 6.5 ± 1.0 years) were assessed using nine high-speed cameras on a treadmill at a speed of 16 km·h⁻¹. Concurrently, isokinetic hip strength was measured at a speed of 60 deg·s⁻¹ in both the dominant and non-dominant legs. The Pearson correlation coefficient and Paired Samples t-test were utilized. Results: While no significant differences were found in several isokinetic strength measurements, notable differences in running kinematics were observed. Specifically, pelvic drop at midstance (MS) was significantly lower in the DL (5.79 ± 3.00°) compared to the NDL (8.71 ± 1.39°) with a large effect size (t=-4.04, p < 0.001, Cohen's d = 1.25). Additionally, knee adduction at maximum showed a moderate effect size difference, with the DL at 2.99 ± 1.13° and the NDL at 3.81 ± 1.76° (t=-2.74, p = 0.03, Cohen's d = 0.55). Results indicated a moderate to highly positive association between running knee adduction in the dominant leg and hip external rotation (r = 0.67, p < 0.05), concentric extension (r = 0.77, p < 0.05), and concentric abduction (r = 0.78, p < 0.05). Additionally, the running tibial external rotation angle in the dominant leg exhibited an inverse relationship with all strength measurements, with statistical significance observed only for concentric extension force (r=-0.68, p < 0.05). Furthermore, hip internal rotation force demonstrated a highly inverse correlation with foot pronation in the dominant leg (r=-0.70, p < 0.05) and anterior pelvic tilt in the non-dominant leg (r=-0.76, p < 0.05). Conclusions: These findings underscore the interrelation between hip strength and running kinematics, particularly on the dominant side. In light of these observations, it is imperative to consider hip strength exercises as integral components for correcting running kinematics. Coaches should also be mindful that kinematic deviations contributing to running injuries may manifest unilaterally or specifically in the dominant leg. [ABSTRACT FROM AUTHOR]

The aim of this study was to examine the possession (very low, low, high, and very high), team formation (3-5-2 and 4-3-3) and position (centre-backs, full-backs, centre midfielders, attacking midfielders, and centre forwards) on match load across two consecutive seasons in elite soccer. Twenty-seven English Premier League outfield players were recruited. Data was monitored through an 18 Hz Global Positioning System and a 25 Hz semi-automated camera tracking system, respectively, and all variables were analysed per minute. Main effects for formation on total distance (TD) (p = 0.006; η² = 0.010), high-speed running (HSR) (p = 0.009; η² = 0.009), number of high metabolic load (HML) efforts (p = 0.004; η² = 0.011) were observed. In addition, there were significant interaction effects with formation x possession on TD (p < 0.001; η² = 0.043), HSR (p = 0.006; η² = 0.018), sprinting (p < 0.001; η² = 0.030), HML efforts (p < 0.001; η² = 0.035), accelerations (p < 0.001; η² = 0.025). From the position-specific analysis, only the running performance of centre-backs was affected by formation or positional factors. These results indicate that formation and possession can have a significant impact on TD, HSR, and HML distance. Furthermore, players performed more high-intensity efforts in 3-5-2 than 4-3-3 formation. These findings suggest that coaches can evaluate running performance in the context of formation and possession and tailor tactical strategies to optimise physical performance. [ABSTRACT FROM AUTHOR]

This study aimed to examine the impact of playing position (PP), match location (ML), and opposition standard (OS) on team and individual acceleration (ACC) and deceleration (DEC) efforts. Fifty professional football players were monitored across 24 English Premier Development League matches during the 2020/21 season. High-intensity ACC and DEC thresholds were set at > +3 m ⋅ s-2 and < -3 m ⋅ s-2, respectively. Players were divided into five PPs: centre backs (CB; n = 68), full-backs (FB; n = 24), centre midfielders (CM; n = 54), wide midfielders (WM; n = 15), centre forwards (CF; n = 27). Opposition standard was categorised as Top (1st-4th), Middle (5th-9th), and Bottom (9th-13th) based on final league ranking of the study season. Each match location was classified as Home or Away. One way analysis of variance (ANOVA) and a multivariate ANOVA analysed the independent effect of PP, ML and OS on ACC and DEC efforts, and the interaction of all contextual factors, respectively. Acceleration efforts were affected by PP and ML. FB performed 22% more ACC than WM. All players performed 6% more ACC actions during home matches compared to away fixtures. DEC efforts were only affected by PP, with FB and CM executing 26% and 32% greater DEC efforts than CB, respectively. When playing against top or middle teams at home, CB, CM, and CF tended to perform more high-intensity actions than when playing away. In contrast, when playing against top teams at home, FB and WM performed fewer high-intensity actions than when playing away. Playing position and ML affected ACC and DEC actions but not OS. [ABSTRACT FROM AUTHOR]

Utilizing techniques for reducing multivariate data is essential for comprehensively understanding the variations and relationships within both biomechanical and physiological datasets in the context of youth football training. Therefore, the objective of this study was to identify the primary factors influencing training sessions within a standard microcycle among young sub-elite football players. A total of 60 male Portuguese youth sub-elite footballers (15.19 ± 1.75 years) were continuous monitored across six weeks during the 2019–2020 in-season, comprising the training days from match day minus (MD-) 3, MD-2, and MD-1. The weekly training load was collected by an 18 Hz global positioning system (GPS), 1 Hz heart rate (HR) monitors, the perceived exertion (RPE) and the total quality recovery (TQR). A principal component approach (PCA) coupled with a Monte Carlo parallel analysis was applied to the training datasets. The training datasets were condensed into three to five principal components, explaining between 37.0% and 83.5% of the explained variance (proportion and cumulative) according to the training day (p < 0.001). Notably, the eigenvalue for this study ranged from 1.20% to 5.21% within the overall training data. The PCA analysis of the standard microcycle in youth sub-elite football identified that, across MD-3, MD-2, and MD-1, the first was dominated by the covered distances and sprinting variables, while the second component focused on HR measures and training impulse (TRIMP). For the weekly microcycle, the first component continued to emphasize distance and intensity variables, with the ACC and DEC being particularly influential, whereas the second and subsequent components included HR measures and perceived exertion. On the three training days analyzed, the first component primarily consisted of variables related to the distance covered, running speed, high metabolic load, sprinting, dynamic stress load, accelerations, and decelerations. The high intensity demands have a high relative weight throughout the standard microcycle, which means that the training load needs to be carefully monitored and managed. [ABSTRACT FROM AUTHOR]

The prevalence of the Relative Age Effect (RAE) was studied among medalists from the World Athletics Championships at U18, U20 and Senior age groups and from the Olympic Games from 2000 to 2022. The specific events examined were the 100, 200, 400, 800, 1500, and 3000/5000 m, the long jump, the triple jump, the high jump and the pole vault. Dates of birth from 1,858 outdoor track and field athletes were analysed and further divided into four groups according to the quartile of birth. The RAE was found to be widespread among athletes of both sexes in U18 and U20 age groups in all examined disciplines. There was no difference between the most successful U18 and U20 athletes (p = 0.52). Among senior athletes of both sexes, this effect was not detected and the number of "late-born" athletes in this age group was higher than athletes born in the first three quarters. The prevalence of the RAE across the four groups of events was found in U18 and U20 age groups. Additionally, within each age group, the difference among events was statistically significant. In most successful track and field athletes, the RAE is only significant in U18 and U20 age groups. In senior athletes, the number of "late-born" athletes is significant while RAE disappears. These data may be considered when assessing the athletic potential of an individual athlete. [ABSTRACT FROM AUTHOR]

Objectives: To explore the differences in training and match load in English Premier League (EPL) 1st team and U23 players. Identifying differences in relative and absolute physical outputs in relation to Maximal Aerobic Speed (MAS) and Maximal Sprint Speed (MSS) and how this informs monitoring and training prescription. Methods: Two groups of full-time professional football players (1st team, n = 24 and U23 squad, n = 27) participated in this study. Training and match data were categorised into weekly blocks from Monday to Sunday. Each player's weekly total was then averaged to provide a squad average for each metric examined. Results: Match analysis identified significantly higher distance covered above 120% MAS and distance between 120% MAS and 85% MSS (p =.04, effect size [ES] = 0.64; p <.01, ES = 1.13) for the 1st team. Distance above 85% MSS was significantly higher for the U23's (p <.01, ES = 2.92). Training and match data during one-match weeks displayed significantly higher differences in all high-speed variables for 1st team players compared to U23 players (p ≤.05, ES = 0.82–1.78). Analysis of training and match data during a two-match week displayed no significant differences for all physical variables (p >.05). Conclusions: Practitioners should consider the utilisation of individual relative thresholds to identify differences between physical performance variables during training and matches for 1st team and U23 players. Utilising these comparisons to inform training design, could maximise players physical development and potential for successful transition. Importantly, these findings relate to only one EPL club and therefore practitioners should assess their own players' relative training and game outputs. [ABSTRACT FROM AUTHOR]

Background: Football matches and training sessions can induce metabolic and mechanical stress, leading to inflammation, oxidative stress, and muscle damage, all of which may negatively impact subsequent performance. Montmorency tart cherry, rich in phytochemicals and anthocyanins, is believed to aid in recovery and alleviate muscle soreness. Similarly, chocolate milk may promote glycogen synthesis, protein synthesis, and rehydration. The aim of this study is to review the effects of cherry juice and chocolate milk on athletes and summarize results to inform future research on football recovery. Methods: This comprehensive review identified relevant literature through an extensive search of the PubMed, Scopus, ScienceDirect, and SPORTDiscus databases, using combinations of keywords related to cherry juice, chocolate milk, and exercise. Studies were selected based on specific inclusion and exclusion criteria. Results: A total of 372 studies were identified through the search [Cherry juice: n = 137; Chocolate milk: n = 235]. After assessing eligibility, 27 studies were included based on the inclusion and exclusion criteria [Cherry juice: n = 14; Chocolate milk: n = 13]. These studies investigated the effects of cherry juice and chocolate milk on various aspects of post-training or post-competition recovery, including muscle damage, inflammation, oxidative stress, and physical performance in athletes from different sports. Conclusion: Based on the reviewed literature, the ingestion of cherry juice and chocolate milk has the potential to reduce muscle damage and soreness and enhance recovery after exercise and physical activities in athletes from various sports. These positive results suggest that cherry juice and chocolate milk may also benefit football players as recovery strategies. However, further research is needed to determine the optimal dosage, timing, and duration of supplementation, as well as the long-term effects on recovery and performance in football-specific contexts. [ABSTRACT FROM AUTHOR]